Triple
T652665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night Journey of Muhammad |
E11377
|
entity |
| Predicate | quranicSurahNumber |
P15360
|
FINISHED |
| Object | 17 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 17 | Statement: [Night Journey of Muhammad, quranicSurahNumber, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quranicSurahNumber Context triple: [Night Journey of Muhammad, quranicSurahNumber, 17]
-
A.
quranicSurah
chosen
Indicates that one entity is a chapter (surah) of the Quran associated with or identified by the other entity.
-
B.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
C.
approximateNumberOfVerses
Indicates an estimated or approximate count of verses associated with an entity.
-
D.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
E.
sacramentNumber
Indicates the specific ordinal position or count assigned to a sacrament within a defined set or sequence of sacraments.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4a660c8190b887cb4da01ef7ae |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d1001088190aa7ca3c8f2ad0e32 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.